A nomogram for predicting invasiveness of lung adenocarcinoma manifesting as ground-glass nodules based on follow-up CT imaging
The nomogram based on morphological features and quantitative parameters from follow-up CT images showed good discrimination and calibration abilities in predicting the invasiveness of lung adenocarcinoma manifesting as GGNs.
Authors
- Hanting Li (ORCID: https://orcid.org/0009-0004-1536-5958)
- Leqing Chen (ORCID: https://orcid.org/0000-0002-4984-965X)
- Heshui Shi (ORCID: https://orcid.org/0000-0001-7644-3711)
- Chengyu Ding
- Yuting Zheng (ORCID: https://orcid.org/0000-0002-2326-9067)
- Xiaoqing Liu
- Jun Fan (ORCID: https://orcid.org/0000-0002-5445-437X)
- Tingting Guo (ORCID: https://orcid.org/0009-0009-2547-0256)
- Jinrong Yang (ORCID: https://orcid.org/0000-0002-7678-0360)
- Xiaoyu Han (ORCID: https://orcid.org/0000-0001-6121-596X)
- Qinyue Luo
Institutions
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
- Wuhan Union Hospital (CN)
- Bayer (China) (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Translational Lung Cancer Research
- Published
- 2024-10-01
- DOI
- https://doi.org/10.21037/tlcr-24-492
- Citations
- 4
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.68
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hubei Province